Methods and apparatus to select virtualization environments for migration

ABSTRACT

Methods and apparatus to select virtualization environments are disclosed. An example method includes determining, via a processor, characteristics of a virtualized application that is deployed in an existing virtualization environment, analyzing, via the processor, the characteristics of the virtualized application to select a subset of virtualization environments that are capable of executing the virtualized application, the subset of virtualization environments selected from a set of virtualization environments of different virtualization environment types used in the datacenter, comparing, via the processor, the characteristics of the virtualized application to the virtualization environments of the subset of virtualization environments to determine scores for the virtualization environments, and migrate the virtualized application from the existing virtualization environment to a new virtualization environment based on the scores.

CROSS-REFERENCE TO RELATED APPLICATION(S)

Benefit is claimed under 35 U.S.C. 119(a)-(d) to Foreign applicationSerial No. 1094/CHE/2015 filed in India entitled “METHODS AND APPARATUSTO SELECT VIRTUALIZATION ENVIRONMENTS FOR MIGRATION”, on Mar. 5, 2015,by VMware, Inc., which is herein incorporated in its entirety byreference for all purposes.

FIELD OF THE DISCLOSURE

This disclosure relates generally to virtual computing, and, moreparticularly, to methods and apparatus to select virtualizationenvironments.

BACKGROUND

Virtualizing computer systems provides benefits such as the ability toexecute multiple computer systems on a single hardware computer,replicating computer systems, moving computer systems among multiplehardware computers, and so forth.

“Infrastructure-as-a-Service” (also commonly referred to as “IaaS”)generally describes a suite of technologies provided by a serviceprovider as an integrated solution to allow for elastic creation of avirtualized, networked, and pooled computing platform (sometimesreferred to as a “cloud computing platform”). Enterprises may use IaaSas a business-internal organizational cloud computing platform(sometimes referred to as a “private cloud”) that gives an applicationdeveloper access to infrastructure resources, such as virtualizedservers, storage, and networking resources. By providing ready access tothe hardware resources required to run an application, the cloudcomputing platform enables developers to build, deploy, and manage thelifecycle of a web application (or any other type of networkedapplication) at a greater scale and at a faster pace than ever before.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an example virtual computing environment inwhich a virtualization platform manager as may operate as disclosedherein.

FIG. 2 is a block diagram of an example implementation of thevirtualization platform manager.

FIGS. 3-7 are flowcharts representative of machine readable instructionsthat may be executed to implement the example virtualization platformmanager of FIGS. 1 and/or 2.

FIG. 8 is a block diagram of an example processing platform capable ofexecuting the example machine-readable instructions of FIGS. 3-7 toimplement the example virtualization platform manager of FIGS. 1 and/or2.

DETAILED DESCRIPTION

Example systems for virtualizing computer systems are described in U.S.patent application Ser. No. 11/903,374, entitled “METHOD AND SYSTEM FORMANAGING VIRTUAL AND REAL MACHINES,” filed Sep. 21, 2007, and granted asU.S. Pat. No. 8,171,485, U.S. Provisional Patent Application No.60/919,965, entitled “METHOD AND SYSTEM FOR MANAGING VIRTUAL AND REALMACHINES,” filed Mar. 26, 2007, and U.S. Provisional Patent ApplicationNo. 61/736,422, entitled “METHODS AND APPARATUS FOR VIRTUALIZEDCOMPUTING,” filed Dec. 12, 2012, all three of which are herebyincorporated herein by reference in their entirety.

Physical computing environments include physical computing resourcessuch as servers, storage devices, etc. Physical computing resources maybe expensive to maintain and/or may require specialized knowledge tooperate and/or service. Virtual computing environments (sometimesreferred to as “virtual data centers”) virtualize such physicalresources or physical components making it possible for someone who doesnot actually own the physical computing resources (e.g., servers,storage components and networks) to utilize the physical computingresources through commercial transactions. Virtualizing aggregates andpresents various physical resources as virtual resources in a virtualcomputing environment. Additionally or alternatively, virtualizationallows for the segregation of workloads executing on the same hardwareor same pool of hardware resources. A workload, as used herein, is anabstraction of work that an application instance or a set ofapplications instances are to perform. For example, a workload may beimplementing a web server, a payment processing server, implementing aweb server farm, implementing a multilayer application, etc. Thus,virtualization allows for a web server and a payment processing serverexecuting on the same underlying hardware to be segregated, have accessto separate virtual hardware, etc.

Many different types of virtualization environments exist. Three exampletypes of virtualization environment are: full virtualization,paravirtualization, and operating system virtualization.

Full virtualization, as used herein, is a virtualization environment inwhich hardware resources are managed by a hypervisor to provide virtualhardware resources to a virtual machine. In a full virtualizationenvironment, the virtual machines do not have access to the underlyinghardware resources. In a typical full virtualization, a host operatingsystem with embedded hypervisor (e.g., VMware ESXi®) is installed on theserver hardware. Virtual machines including virtual hardware resourcesare then deployed on the hypervisor. A guest operating system isinstalled in the virtual machine. The hypervisor manages the associationbetween the hardware resources of the server hardware and the virtualresources allocated to the virtual machines (e.g., associating physicalrandom access memory (RAM) with virtual RAM). Typically, in fullvirtualization, the virtual machine and the guest operating system haveno visibility and/or access to the hardware resources of the underlyingserver. Additionally, in full virtualization, a full guest operatingsystem is typically installed in the virtual machine while a hostoperating system is installed on the server hardware. Examplevirtualization environments include VMware ESX®, Microsoft Hyper-V®, andKernel Based Virtual Machine (KVM).

Paravirtualization, as used herein, is a virtualization environment inwhich hardware resources are managed by a hypervisor to provide virtualhardware resources to a virtual machine and guest operating systems arealso allowed to access to some or all of the underlying hardwareresources of the server (e.g., without accessing an intermediate virtualhardware resource). In a typical paravirtualization system, a hostoperating system (e.g., a Linux-based operating system) is installed onthe server hardware. A hypervisor (e.g., the Xen® hypervisor) executeson the host operating system. Virtual machines including virtualhardware resources are then deployed on the hypervisor. The hypervisormanages the association between the hardware resources of the serverhardware and the virtual resources allocated to the virtual machines(e.g., associating physical random access memory (RAM) with virtualRAM). In paravirtualization, the guest operating system installed in thevirtual machine is configured also to have direct access to some or allof the hardware resources of the server. For example, the guestoperating system may be precompiled with special drivers that allow theguest operating system to access the hardware resources without passingthrough a virtual hardware layer. For example, a guest operating systemmay be precompiled with drivers that allow the guest operating system toaccess a sound card installed in the server hardware. Directly accessingthe hardware (e.g., without accessing the virtual hardware resources ofthe virtual machine) may be more efficient, may allow for performance ofoperations that are not supported by the virtual machine and/or thehypervisor, etc.

Operating system virtualization is also referred to herein as containervirtualization. As used herein, operating system virtualization refersto a system in which processes are isolated in an operating system. In atypical operating system virtualization system, a host operating systemis installed on the server hardware. Alternatively, the host operatingsystem may be installed in a virtual machine of a full virtualizationenvironment or a paravirtualization environment. The host operatingsystem of an operating system virtualization system is configured (e.g.,utilizing a customized kernel) to provide isolation and resourcemanagement for processes that execute within the host operating system(e.g., applications that execute on the host operating system). Theisolation of the processes is known as a container. Thus, a processexecutes within a container that isolates the process from otherprocesses executing on the host operating system. Thus, operating systemvirtualization provides isolation and resource management capabilitieswithout the resource overhead utilized by a full virtualizationenvironment or a paravirtualization environment. Example operatingsystem virtualization environments include Linux Containers LXC and LXD,Docker™, OpenVZ™, etc.

In some instances, a data center (or pool of linked data centers) mayinclude multiple different virtualization environments. For example, adata center may include hardware resources that are managed by a fullvirtualization environment, a paravirtualization environment, and anoperating system virtualization environment. In such a data center, aworkload may be deployed to any of the virtualization environments.

Some methods and apparatus disclosed herein analyze characteristics of aworkload to be deployed and characteristic of available virtualizationenvironments to determine a virtualization environment in which todeploy the workload. Some methods and apparatus disclosed herein analyzea workload deployed in a first virtualization environment to determineif the workload should be migrated to a second virtualizationenvironment (of the available virtualization environments). In some suchmethods and apparatus, the first virtualization environment receives afirst score for execution of the workload based on the analysis of theworkload, the second virtualization environment receives a second scorefor execution of the workload based on the analysis of the workload, andthe workload is migrated when the second score exceeds (or meets) thefirst score.

FIG. 1 is a block diagram of an example virtual computing environment100 in which a virtualization platform manager 112 may operate asdisclosed herein.

The example virtual computing environment 100 of FIG. 1 includes anexample network of storage arrays 102 in communication with examplecomputing servers 104. The example network of storage arrays 102 may beimplemented using any suitable wired and/or wireless storage including,for example, one or more Fiber Channel Storage Area Network (SAN)arrays, one or more Internet Small Computer System Interface (iSCSI) SANarrays, one or more Network Attached Storage (NAS) arrays, etc. In theillustrated example, the network of storage arrays 102 are connected toand shared between groups of servers 104 through storage area networks,thereby enabling aggregation of storage resources and enabling increasedflexibility in provisioning the storage resources to, for example,example virtualization platforms 107, 108, and 109. While the examplevirtual computing environment 100 includes a single storage array 102connected to each of the computing servers 104 any number of storagearrays 102 may be utilized and any other type of shared and non-sharedstorage hardware may be utilized (e.g., hard drives installed in each ofthe computing servers 104, cloud based on storage resources, etc.).

In the illustrated example of FIG. 1, the example servers 104 may be ×86servers in communication with the example network of storage arrays 102via an example network 106. The network 106 of FIG. 1 may be implementedusing any suitable wired and/or wireless network(s) such as, forexample, one or more data buses, one or more Local Area Networks (LANs),one or more wireless LANs, one or more cellular networks, the Internet,etc.

The example virtualization platforms 108-109 of FIG. 1 execute oncorresponding ones of the example computing servers 104. According tothe illustrated example, the example first virtualization platform 107implements a full virtualization environment in which example virtualmachines 110 execute. The example second virtualization platform 108implements a paravirtualization environment in which example virtualmachines 115 execute. The example third virtualization platform 108implements an operating system virtualization environment in whichexample applications 120 execute within containers created by theexample third virtualization platform 109. In other implementations anynumber and/or combination of virtualization platforms and virtualizationenvironments may be utilized.

The example virtualization platforms 107-109 include management toolsand systems to facilitate management of the virtualization platforms107-109. For example, management tools may provide access for anadministrator to configure the virtual machines 110, 115 and/orcontainers for the applications 120. Additionally or alternatively,management tools may provide access for an administrator to configureallocation of the hardware resources of the example servers 104 to thevirtualization platforms 107-109. The example virtualization platforms107-109 may each include separate management tools and systems and/ormanagement tools and systems may be provided for managing the entirevirtual computing environment 100. For example, the virtual computingenvironment 100 may include a cloud management administration system(e.g., the VMware vCloud Automation Center®).

The example virtualization platform 100 includes a first workload 140that is awaiting deployment. For example, the workload 140 may be a webserver, a database server, a credit card processing server, etc. thatneeds to be deployed on a virtualization platform for execution. Theexample virtualization platform 100 additionally includes a secondworkload 141 that is deployed on one of the example virtual machines 110executing in the example first virtualization platform 107. While thetwo workloads 140, 141 are provided as examples, any number ofto-be-deployed and deployed workloads may be included in animplementation of the example virtual environment 100.

To manage the example virtual computing environment 100, the examplevirtual computing environment 100 of FIG. 1 includes the examplevirtualization platform manager 112. The example virtualization platformmanager 112 manages assignment of workloads (e.g., the example workload140 and the example workload 141) to ones of the example virtualizationplatforms 107-109. According to the illustrated example, thevirtualization platform manager 112 is invoked upon receipt of a requestto deploy a new workload in the example virtual environment 100. Forexample, the virtualization platform manager 112 may receive a requestfrom a user utilizing a management client 114, may receive a requestfrom an environment management tool (e.g., a cloud management tool),etc. The example virtualization platform manager 112 is also invoked toreview deployed workloads to determine if a workload should be migratedfrom one virtualization platform 107-109 to another virtualizationplatform 107-109. For example, the virtualization platform manager 112may be configured to automatically, periodically (e.g., according to aschedule) analyze deployed workloads, aperiodically analyze deployedworkloads, analyze a deployed workload upon a request from a userutilizing the management client 114, analyze all deployed workloads upona request from a user utilizing the management client 114, etc.

Once invoked, the example virtualization platform manager 112 analyzescharacteristics of a workload of interest (e.g., the example workload140 that is to be deployed or the example deployed workload 141 that isconsidered for migrating from the example virtualization platform 107 toanother one of the example virtualization platforms 107-109) andcharacteristics of the example virtualization platforms 107-109 todetermine which one(s) of the example virtualization platforms 107-109may be utilized for the workload 141, 140 (e.g., which ones of theexample virtualization platforms 107-109 are compatible with theworkload 140, 141). When more than one of the example virtualizationplatforms 107-109 may be utilized for the workload 140, 141, the examplevirtualization platform manager 112 further analyzes the characteristicsof the workload 140, 141 and the characteristics of the examplevirtualization platforms 107-109 to determine scores for the examplevirtualization platforms 107-109 (e.g., determines a score for each ofthe virtualization platforms 107-109 that were determined to becompatible with the workload 140, 141). The example virtualizationplatform 107-109 deploys or migrates the workload 140, 141 to the one ofthe example virtualization platforms 107-109 that has the best score(e.g., the highest score, the lowest score, etc.). The examplevirtualization platform manager 112 may additionally include operationsfor handling situations when two or more of the virtualization platforms107-109 receive equivalent scores (e.g., randomly assigning to one ofthe equivalently scored virtualization platforms 107-109, assigning toone of the equivalently scored virtualization platforms 107-109 in aneffort to balance the load on the virtualization platforms 107-109etc.).

FIG. 2 is a block diagram of an example implementation of thevirtualization platform manager 112. The example virtualization platformmanager 112 of FIG. 2 includes an example workload analyzer 202, anexample virtualization environment analyzer 204, an example feasibilityanalyzer 206, an example configuration datastore 208, an example scoregenerator 210, an example workload deployer 212, and an example workloadmigrator 214.

The example workload analyzer 202 of FIG. 2 analyzes a workload (e.g.,the example workload 140 and/or the example workload 141) for which avirtualization platform (e.g., the first virtualization platform 107,the second virtualization platform 108, and/or the third virtualizationplatform 109) is to be selected. The example workload analyzer 202analyzes the workload 140, 141 to determine characteristics of theworkload 140, 141. For example, the workload analyzer 202 may analyzeconfiguration information for the workload 140, 141 (e.g., aconfiguration file created during development/creation of the workload140, 141, configuration settings of the workload 140, 141, etc.). Theexample workload analyzer 202 determines:

A) computing resource settings, requirements, requests, etc. for theworkload 140, 141,

B) an operating system of the workload 140, 141 (e.g., a Linux basedoperating system, Microsoft Windows®, etc.),

C) networking requirements of the workload 140, 141,

D) whether or not the workload 140, 141 includes a group of elements(e.g., a VMware® vApp or other bundle of virtual machines and/orapplications), and

E) whether or not the workload 140, 141 will need to be upgraded at alater time (e.g., upgraded by the installation of security patches).

The example workload analyzer 202 may additionally or alternativelygather any other characteristic and/or status information regarding theworkload 140, 141. For example, the example workload analyzer 202 maydetermine the operating status of the workload 140, 141 (e.g., theworkload analyzer 202 may determine if the workload 141 is executingand/or is at a state at which the workload 141 can be migrated).

After gathering characteristics for the example workload 140, 141, theexample workload analyzer 202 provides the characteristic information tothe example feasibility analyzer 206 and the example score generator210. Additionally, the example workload analyzer 202 providesinformation about the workload 140, 141 to the workload deployer 212and/or the workload migrator 214 for use in deploying the workload 140,141 and/or migrating the workload 140, 141, respectively.

The example virtualization environment analyzer 204 analyzes the examplevirtualization platforms 107-109 of the example virtual computingenvironment 100 to determine characteristics of the virtualizationplatforms 107-109. The example virtualization environment analyzer 204gathers characteristic information for the virtualization platforms107-109 by querying application programming interfaces (APIs) ofmanagement platforms of the virtualization platforms 107-109. Thevirtualization environment analyzer 204 may additionally oralternatively analyze configuration information for the virtualizationplatforms 107-109 by accessing a configuration file associated with thevirtualization platforms 107-109, accessing configuration settings ofthe virtualization platforms 107-109, accessing operating statusinformation for the virtualization platforms 107-109, etc.

The example virtualization environment analyzer 204 determines:

A) operating systems utilized by the virtualization platforms 107-109andB) computing resources available in the virtualization platforms107-109.

The virtualization environment analyzer 204 may additionally oralternatively gather any other characteristic and/or status informationregarding the virtualization platforms 107-109.

After gathering characteristics for the example virtualization platforms107-109, the example virtualization environment analyzer 204 providesthe characteristic information to the example feasibility analyzer 206and the example score generator 210.

The example feasibility analyzer 206 of FIG. 2 retrieves configurationinformation from the example configuration datastore 208 and, using theconfiguration information, compares the configuration information to thecharacteristics of the workload 140, 141 and the characteristics of thevirtualization platforms 107-109 to determine which of thevirtualization platforms 107-109 are capable of executing the workload140, 141. An example process for determining feasibility information forexecuting the workload 140, 141 in the example virtualization platforms107-109 is described in conjunction with FIG. 5#.

The example configuration datastore 208 of FIG. 2 stores configurationinformation for use in selecting one of the virtualization platforms107-109 for deploying and/or transitioning the workload 140, 141. Theexample configuration datastore 208 stores file containing a first setof rules for determining which of the virtualization platforms 107-109are capable of executing the workload 140, 141 and a second set of rulesfor scoring the virtualization platforms 107-109 for execution of theworkload 140, 141. Alternatively, a single set of rules may be storedand/or additional sets of rules or other configuration information maybe stored.

The configuration datastore 208 may be implemented by any type ofstorage device such as, for example, a hard disk, a flash drive, anetwork attached storage, the example storage array 102, or any othertype of storage. Additionally, the configuration datastore 208 may storeconfiguration in any type of format such as, for example, a commaseparated values (CSV) file, an extensible markup language (XML) file,etc.

The example score generator 210 of FIG. 2 retrieves configurationinformation from the example configuration datastore 208 and, using theconfiguration information, compares the configuration information to thecharacteristics of the workload 140, 141 and the characteristics of thevirtualization platforms 107-109 to determine scores for thevirtualization platforms 107-109 for executing the workload 140, 141.The example score generator 210 receives an identification of one(s) ofthe virtualization platforms 107-109 that are capable of executing theworkload 140, 141. The score generator 210 of the illustrated exampledetermines a score for each of the virtualization platforms 107-109 thatare capable of executing the workload 140, 141 according to thefeasibility analyzer 206. Thus, the example score generator 210 does notexpend computing resources generating scores for ones of thevirtualization platforms 107-109 that are not capable of executing theworkload 140, 141. An example process for determining a score isdescribed in conjunction with FIGS. 6# and 7#.

After generating scores for the example virtualization platforms107-109, the example score generator 210 of FIG. 2 identifies theselected one of the virtualization platforms 107-109 that has the bestscore (e.g., the highest score, the lowest score, etc.). The scoregenerator 210 identifies the selected one of the virtualizationplatforms 107-109 to the example workload deployer 212 and the exampleworkload migrator 214. An example process for determining scoreinformation for executing the workload 140, 141 in the examplevirtualization platforms 107-109 is described in conjunction with FIG.6#.

The example workload deployer 212 of FIG. 2 receives information aboutthe workload 140, 141 from the example workload analyzer 202 and, whenthe workload 140, 141 is a workload that is to be newly deployed (e.g.,the example workload 140), the workload deployer 212 deploys theworkload 140, 141 in the virtualization platform 107-109 identified bythe example score generator 210. For example, the example workloaddeployer 212 may transfer the data of the workload 140, 141 to thestorage array 102 and cause the workload 140, 141 to be executed on theselected one of the virtualization platforms 107-109 identified by thescore generator 210.

The example workload migrator 214 of FIG. 2 receives information aboutthe workload 140, 141 from the example workload analyzer 202 and, whenthe workload 140, 141 is a workload that is to be migrated from a firstone of the virtualization platforms 107-109 to a second one of thevirtualization platforms 107-109 (e.g., the example workload 141), theworkload migrator 214 migrates the workload 140, 141 to thevirtualization platform 107-109 identified by the example scoregenerator 210. For example, the example workload migrator 214 may causethe workload 140, 141 to be turned off, shutdown, suspended, etc. andthen transferred to the selected one of the virtualization platforms107-109 identified by the score generator 210. In another example, theworkload migrator 214 may invoke a online conversion in which theworkload is analyzed while executing until the workload is fullytransferred and then the workload is stopped on the old platform andstarted on the new platform. Alternatively, any other process formigrating the workload 140, 141 may be utilized.

While an example manner of implementing the example virtualizationplatform manager 112 of FIG. 1 is illustrated in FIG. 2, one or more ofthe elements, processes and/or devices illustrated in FIG. 2 may becombined, divided, re-arranged, omitted, eliminated and/or implementedin any other way. Further, the example workload analyzer 202, theexample virtualization environment analyzer 204, the example feasibilityanalyzer 206, the example score generator 210, the example workloaddeployer 212, the example workload migrator 214 and/or, more generally,the example virtualization platform manager 112 of FIG. 1 may beimplemented by hardware, software, firmware and/or any combination ofhardware, software and/or firmware. Thus, for example, any of theexample workload analyzer 202, the example virtualization environmentanalyzer 204, the example feasibility analyzer 206, the example scoregenerator 210, the example workload deployer 212, the example workloadmigrator 214 and/or, more generally, the example virtualization platformmanager 112 of FIG. 1 could be implemented by one or more analog ordigital circuit(s), logic circuits, programmable processor(s),application specific integrated circuit(s) (ASIC(s)), programmable logicdevice(s) (PLD(s)) and/or field programmable logic device(s) (FPLD(s)).When reading any of the apparatus or system claims of this patent tocover a purely software and/or firmware implementation, at least one ofthe example workload analyzer 202, the example virtualizationenvironment analyzer 204, the example feasibility analyzer 206, theexample score generator 210, the example workload deployer 212, and/orthe example workload migrator 214 is/are hereby expressly defined toinclude a tangible computer readable storage device or storage disk suchas a memory, a digital versatile disk (DVD), a compact disk (CD), aBlu-ray disk, etc. storing the software and/or firmware. Further still,the example virtualization platform manager 112 of FIG. 1 may includeone or more elements, processes and/or devices in addition to, orinstead of, those illustrated in FIG. 2, and/or may include more thanone of any or all of the illustrated elements, processes and devices.

Flowcharts representative of example machine-readable instructions forimplementing the virtualization platform manager 112 FIGS. 1 and/or 2are shown in FIGS. 3-7. In this example, the machine-readableinstructions comprise a program for execution by a processor such as theprocessor 812 shown in the example processor platform 800 discussedbelow in connection with FIG. 8. The program may be embodied in softwarestored on a tangible computer readable storage medium such as a CD-ROM,a floppy disk, a hard drive, a digital versatile disk (DVD), a Blu-raydisk, or a memory associated with the processor 812, but the entireprogram and/or parts thereof could alternatively be executed by a deviceother than the processor 812 and/or embodied in firmware or dedicatedhardware. Further, although the example program is described withreference to the flowcharts illustrated in FIGS. 3-7, many other methodsof implementing the example virtualization platform manager 112 mayalternatively be used. For example, the order of execution of the blocksmay be changed, and/or some of the blocks described may be changed,eliminated, or combined.

FIG. 3# is a flowchart of example machine readable instructions that maybe executed to deploy a new workload (e.g., the workload 140 of FIG. 1).The process of FIG. 3# begins when the workload analyzer 202 receivesthe new workload 140 to be deployed (block 3#02). For example, the newworkload 140 may be identified by a user utilizing the examplemanagement client 114 of FIG. 1, may be received from a cloud managementtool, etc. The example virtualization platform manager 112 of FIGS. 1and 2 then, as described in conjunction with the process 5#00 of FIG. 5,determines which of the example virtualization platforms 107-109 of FIG.1 are capable of performing the example workload 140 (block 5#00). Theexample virtualization platform manager 112 then, as described inconjunction with the process 6#00 of FIG. 6#, determines which one ofthe example virtualization platforms 107-109 (of the virtualizationplatforms 107-109 determined to be capable of executing the workload 140in block 5#00) received the best score (block 6#00). The exampleworkload deployer 212 of FIG. 2 then deploys the new workload 140 in oneof the visualization platforms 107-109 identified in block 6#00 (block3#04).

FIG. 4# is a flowchart of example machine readable instructions that maybe executed to migrate a workload (e.g., the workload 141 of FIG. 1)that is currently deployed on a first virtualization platform (e.g., theexample first virtualization platform 107) to a second virtualizationplatform (e.g., the example third virtualization platform 109). Theprocess of FIG. 4# begins when the workload analyzer 202 receives anidentification of the deployed workload 141 to be migrated (block 4#02).For example, the workload 141 may be identified during a periodic reviewof deployed workloads, may be identified by a user utilizing the examplemanagement client 114 of FIG. 1, etc. The example virtualizationplatform manager 112 of FIGS. 1 and 2 then, as described in conjunctionwith the process #00 of FIG. 5#, determines which of the examplevirtualization platforms 107-109 of FIG. 1 are capable of performing theexample workload 141 (block 5#00). The example virtualization platformmanager 112 then, as described in conjunction with the process 6#00 ofFIG. 6#, determines which one of the example virtualization platforms107-109 (of the virtualization platforms 107-109 determined to becapable of executing the workload 141 in block 5#00) received the bestscore (block 6#00).

The example workload migrator 214 of FIG. 2 then determines the currentvirtualization platform 107-109 in which the workload 141 is deployed(block 4#04). The workload migrator 214 determines if the virtualizationplatform 107-109 identified in block 6#00 is the same as the currentvirtualization platform 107-109 in which the workload 141 is alreadydeployed (block 4#06). If the workload 141 is already deployed in thevirtualization platform 107-109 identified in block 6#00, the process ofFIG. 4# ends.

If the workload 141 is not already deployed in the virtualizationplatform 107-109 identified in block 6#00 (block 4#06), the exampleworkload migrator 214 migrates the workload 141 from the current one ofthe virtualization platforms 107-109 to the one of the virtualizationplatforms 107-109 identified in block 6#00 (block 4#08). For example,the workload migrator 214 may cause the deployed workload 141 to besuspended and/or shutdown, exported from the current virtualizationplatform 107-109, imported into the virtualization platform 107-109identified in block 6#00, and woken and/or restarted. Alternatively, theworkload migrator 214 may perform a live migration of the exampleworkload 141 from the current virtualization platform 107-109 to thevirtualization platform 107-109 identified in block 6100.

FIG. 5# is a flowchart illustrating an example process 5#00 to determinefeasibility information for executing the workload 140, 141 on thevirtualization platforms 107-109. The example process of FIG. 5# beginswhen the example feasibility analyzer 206 retrieves feasibilityconfiguration data from the example configuration datastore 208 (block5#02). The process illustrated by blocks 5#04-5#18 is based on the rulesidentified in the feasibility configuration data. The process of blocks5#04-5#18 may vary based on the rules identified in the feasibilityconfiguration data.

The example workload analyzer 202 retrieves an identification of theguest operating system associated with the workload 140, 141 (block5#04). The example feasibility analyzer 206 determines if the guestoperating system identified by the workload analyzer 202 is unmodified(block 5#06). For example, the workload analyzer 202 may determine ifthe guest operating system has a modified kernel. If the guest operatingsystem is modified (e.g., a modified kernel), the example feasibilityanalyzer 206 removes any paravirtualization environments (e.g., thesecond virtualization platform 108) from the set of availablevirtualization platforms (block 5#08).

The example feasibility analyzer 206 then determines if the guestoperating system associated with the workload 140, 141 is supported byoperating system virtualization environments (e.g., the thirdvirtualization platform 109) (block 5#10). When the guest operationsystem is not supported by the operating system virtualizationenvironments, the example feasibility analyzer 206 removes any operatingsystem virtualization environments (e.g., the third virtualizationplatform 109) from the set of available virtualization platforms (block5#18).

If the guest operating system is supported by the operating systemvirtualization environments (block 5#10), the example feasibilityanalyzer 206 then determines if the processing requirements of theworkload 140, 141 allow the use of shares (e.g., shared accesses theprocessing resources) rather than reserved processing resources (block5#12). When the workload 140, 141 requests and/or requires reversedprocessing resources, the example feasibility analyzer 206 removes anyoperating system virtualization environments (e.g., the thirdvirtualization platform 109) from the set of available virtualizationplatforms (block 5#18).

If the processing requirements of the workload 140,141 allow the use ofshares (block 5#12), the example feasibility analyzer 206 thendetermines if the memory requirements of the workload 140, 141 allow theuse of limits (e.g., a maximum amount of shared memory that may beutilized) rather than reserved memory (block 5#14). When the workload140, 141 requests and/or requires reversed memory resources, the examplefeasibility analyzer 206 removes any operating system virtualizationenvironments (e.g., the third virtualization platform 109) from the setof available virtualization platforms (block 5#18).

If the memory requirements allow the use of limits (block 5#14), theexample feasibility analyzer 206 then determines if the networkrequirements of the workload 140, 141 include any requirements thatcannot be handled by the operating system virtualization environments(block 5#16). For example, the workload 140, 141 may require virtualswitch functionality that is not supported by operating systemvirtualization environments. When the workload 140, 141 requests and/orrequires network requires that cannot be handled by operating systemvirtualization environments, the example feasibility analyzer 206removes any operating system virtualization environments (e.g., thethird virtualization platform 109) from the set of availablevirtualization platforms (block 5#18).

After checking feasibility requirements (e.g., blocks 5#06 and5#10-5#16) and removing ones of the virtualization platforms 107-109(e.g., the containers) that do not meet the requirements of the workload140, 141 (e.g., blocks 5#08 and 5#18), the example feasibility analyzer206 communicates supported ones of the example virtualization platforms107-109 to the score generator 210 (block 5#20). For example, thefeasibility analyzer 206 may store an identification of the supportedones of the example virtualization platforms 107-109 in the exampleconfiguration datastore 208.

FIG. 6# is a flowchart illustrating an example process 6#00 to determinescore information for executing the workload 140, 141 on thevirtualization platforms 107-109. The example process of FIG. 6# beginswhen the example score generator 210 retrieves assessment configurationdata from the example configuration datastore 208 (block 6#02).

The score generator 210 determines if more than one of the examplevirtualization platforms 107-109 were identified by the feasibilityanalyzer 206 as supported for executing the workload 140, 141 (block6#04). If only one of the virtualization platforms 107-109 wereidentified as supported (e.g., by the process illustrated in FIG. 5#),the example score generator 210 reports the selected one of thevirtualization platforms 107-109 to the workload deployer 212 and theworkload migrator 214 (block 6#10).

If more than one of the virtualization platforms 107-109 were identifiedas supported (block 6#04), the example score generator 210 analyzes thecharacteristics of the workload 140, 141 and the characteristics of thevirtualization platforms 107-109 (block 6#06). An example process foranalyzing the characteristics of the workload 140, 141 and thecharacteristics of the virtualization platforms 107-109 is described inconjunction with FIG. 7#.

After analyzing the characteristics of the workload 140, 141 and thecharacteristics of the virtualization platforms 107-109, the examplescore generator 210 determines a score for each of the virtualizationplatforms 107-109 (block 6#08). For example, the score generator 210 maytranslate ranking information into numerical scores. According to theillustrated example, the score is associated with a combination of theworkload and the virtualization platform. Thus, if two workloads areanalyzed against three platforms, a first set of scores will begenerated for the first workload (e.g., one score for each platform) andthe greatest score may be selected and a second set of scores (e.g., onescore for each platform) will be generated for the second workload andthe greatest score among the second set of scores may be selected.

The example score generator 210 then determines one of thevirtualization platforms 107-109 with the greatest score and reports theone of the virtualization platforms 107-109 with the greatest score tothe workload deployer 212 and the workload migrator 214 (block 6#10).

FIG. 7# illustrates an example process for scoring the virtualizationplatforms 107-109 for execution of the example workload 140, 141. Theprocess of FIG. 7# may be utilized to implement block 6#06 of FIG. 6#.

The example process of FIG. 7# begins when the virtualizationenvironment analyzer 204 determines an amount of computing resourcesavailable the virtual computing environment 100 (block 7#02). Forexample, the virtualization environment analyzer 204 may query an APIassociated with the virtual computing environment 100 to determine anamount of RAM that is available for allocation to new workloads invirtualization platforms 107-109. The score generator 210 then comparesthe available resources for the virtual computing environment 100 toresource requirements determined the example workload analyzer 202 todetermine if the virtual computing environment has sufficient resourcesto allocate to the workload 140, 141 (block 7#04). If sufficientresources are not available to allocate to the workload 140, 141, thenshared resource, low overhead environments can be utilized (e.g., theoperating system virtualization environments such as the thirdvirtualization platform 109). Accordingly, the full virtualization andparavirtualization environments are tagged with LOW scores and theoperating system virtualization (e.g., container environment) is taggedwith a HIGH score (block 7#06). Alternatively, if sufficient resourcesare available to allocate to the workload 140, 141, all virtualizationenvironments are tagged with the HIGH score (block 7#08).

The score generator 210 then determines if a fast boot time is desiredfor the guest operating system of the workload 140, 141 (block 7#10).For example, the workload analyzer 202 may determine that a fast boottime is desired based on configuration information associated with theworkload 140, 141. Alternatively, the score generator 210 may prompt auser (e.g., utilizing the management client 114) to indicate if a fastboot time for the workload is desired. If a fast boot time is notdesired and/or is not a requirement, no scores are tagged to thevirtualization platforms 107-109 (block 7#12). Alternatively, if a fastboot time is desired and/or is a requirement, the full virtualizationand paravirtualization environments are tagged with LOW scores and theoperating system virtualization is tagged with a HIGH score (block7#14).

The score generator 210 then determines if groups of elements will beprovisioned (e.g., several virtual machines and/or containers thatutilize the same guest operating system (block 7#16). For example, theworkload analyzer 202 may determine that the workload includes a groupof elements by analyzing the information contained in the workload 140,141. Alternatively, the score generator 210 may prompt a user (e.g.,utilizing the management client 114) to indicate if a group of elementsis included in the workload 140, 141 or will be desired. If a group ofelements is not included in the workload 140, 141, no scores are taggedto the virtualization platforms 107-109 (block 7#18). Alternatively, ifa group of elements is included in the workload 140, 141 or will bedesired, the full virtualization environments are tagged with a LOWscore, the paravirtualization environments are tagged with a MEDIUMscore, and the operating system virtualizations are tagged with a HIGHscore (block 7#20).

The score generator 210 then determines if scaleout is needed or desiredfor the workload 140, 141 (block 7#22). For example, the score generator210 may prompt a user (e.g., utilizing the management client 114) toindicate if scaleout will be required or desired. Scaleout is a processby which additional instances of a workload are deployed (e.g., tohandle additional client accesses). If scaleout is not desired, noscores are tagged to the virtualization platforms 107-109 (block 7424).Alternatively, if scaleout is desired, the full virtualizationenvironments and the paravirtualization environments are tagged with aMEDIUM score and the operating system virtualizations are tagged with aHIGH score (block 7#26).

The score generator 210 then determines if the guest operating system ofthe workload 140, 141 will be upgraded at a later time (e.g., willsecurity patches or other upgrades be installed after the workload 140,141 is deployed) (block 7#28). For example, the assessment configurationdata may indicate which guest operating systems utilize securitypatches. Alternatively, the example score generator 210 may prompt auser (e.g., utilizing the management client 114) to indicate if upgradeswill be installed. If upgrades will not be installed, no scores aretagged to the virtualization platforms 107-109 (block 7#30).Alternatively, if upgrades will be installed after deployment of theworkload, the full virtualization environments are tagged with a MEDIUMscore, the paravirtualization environments are tagged with a LOW score,and the operating system virtualizations are tagged with a HIGH score(block 7#32).

The score generator 210 then determines if high availability (HA) (e.g.,failure tolerant, failover capabilities, redundant operation, etc.) isneeded or desired for the workload 140, 141 (block 7#34). For example,the score generator 210 may prompt a user (e.g., utilizing themanagement client 114) to indicate if HA will be required or desired. IfHA is not desired, no scores are tagged to the virtualization platforms107-109 (block 7#36). Alternatively, if HA is desired, the fullvirtualization environments are tagged with a HIGH score and theparavirtualization environments and the operating system virtualizationsare tagged with a LOW score (block 7#38).

The score generator 210 then determines if the workload 140, 141 isutilized in a production environment (e.g., as opposed to a developmentand/or testing environment) (block 7#40). For example, the scoregenerator 210 may prompt a user (e.g., utilizing the management client114) to indicate if workload 140, 141 is and/or will be utilized in aproduction environment. If the workload 140, 141 is not and/or will notbe utilized in a production environment, no scores are tagged to thevirtualization platforms 107-109 (block 7#42). Alternatively, if theworkload 140, 141 is and/or will be utilized in a productionenvironment, the full virtualization environments and theparavirtualization environments are tagged with a HIGH score and theoperating system virtualizations are tagged with a LOW score (block7#44).

Accordingly, in accordance with FIGS. 7# and 1, the first virtualizationplatform 107 is tagged according to the tags assigned to fullvirtualization environments, the second virtualization platform 108 istagged according to the tags assigned to paravirtualizationenvironments, and the third virtualization platform 109 is taggedaccording to the tags assigned to operating system virtualizationenvironments.

Following the tagging of the example virtualization platforms 107-109,the scores of LOW, MEDIUM, and HIGH are assigned numerical values andsummed in block 6#08 of FIG. 6#. For example, the LOW tags may be scoredas a value of 1, the MEDIUM tags may be scored as a value of 2, and theHIGH tags may be scored as a value of 3. In addition, in some examples,a weighted averaging is applied to the scores based on an importance ofeach score as indicated in the assessment configuration data. Forexample, the scores associated with blocks 7#04 and 7#40 may be rankedwith HIGH importance (e.g., a weight of 3), the scores associated withblocks 7#10, 7#22, 7#28, and 7#34 may be ranked with MEDIUM importance(e.g., a weight of 2), and the scores associated with block 7#16 may beranked with a LOW importance (e.g., a weight of 1). The weighted scoresfor of the virtualization platforms 107-109 may be computed bymultiplying the importance values times the associated tagged scores andsumming the products individually for each of the virtualizationplatforms 107-109.

FIG. 8 is a block diagram of an example processor platform 800 capableof executing the instructions of FIGS. 3-7 to implement thevirtualization platform manager 112 of FIGS. 1 and/or 2. The processorplatform 800 can be, for example, a server, a personal computer, amobile device (e.g., a cell phone, a smart phone, a tablet such as aniPad™), a personal digital assistant (PDA), an Internet appliance, orany other type of computing device.

The processor platform 800 of the illustrated example includes aprocessor 812. The processor 812 of the illustrated example is hardware.For example, the processor 812 can be implemented by one or moreintegrated circuits, logic circuits, microprocessors or controllers fromany desired family or manufacturer.

The processor 812 of the illustrated example includes a local memory 813(e.g., a cache). The example processor includes the example workloadanalyzer 202, the example virtualization environment analyzer 204, theexample feasibility analyzer 206, the example score generator 210, theexample workload deployer 212, and the example workload migrator 214 ofFIG. 2 to implement the example virtualization platform manager 112 ofFIGS. 1 and/or 2. The processor 812 of the illustrated example is incommunication with a main memory including a volatile memory 814 and anon-volatile memory 816 via a bus 818. The volatile memory 814 may beimplemented by Synchronous Dynamic Random Access Memory (SDRAM), DynamicRandom Access Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM)and/or any other type of random access memory device. The non-volatilememory 816 may be implemented by flash memory and/or any other desiredtype of memory device. Access to the main memory 814, 816 is controlledby a memory controller.

The processor platform 800 of the illustrated example also includes aninterface circuit 820. The interface circuit 820 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), and/or a PCI express interface.

In the illustrated example, one or more input devices 822 are connectedto the interface circuit 820. The input device(s) 822 permit(s) a userto enter data and commands into the processor 812. The input device(s)can be implemented by, for example, an audio sensor, a microphone, acamera (still or video), a keyboard, a button, a mouse, a touchscreen, atrack-pad, a trackball, isopoint and/or a voice recognition system.

One or more output devices 824 are also connected to the interfacecircuit 820 of the illustrated example. The output devices 824 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay, a cathode ray tube display (CRT), a touchscreen, a tactileoutput device, a printer and/or speakers). The interface circuit 820 ofthe illustrated example, thus, typically includes a graphics drivercard, a graphics driver chip or a graphics driver processor.

The interface circuit 820 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem and/or network interface card to facilitate exchange of data withexternal machines (e.g., computing devices of any kind) via a network826 (e.g., an Ethernet connection, a digital subscriber line (DSL), atelephone line, coaxial cable, a cellular telephone system, etc.).

The processor platform 800 of the illustrated example also includes oneor more mass storage devices 828 for storing software and/or data. Theexample mass storage 828 includes the example configuration datastore208 of FIG. 2. Examples of such mass storage devices 828 include floppydisk drives, hard drive disks, compact disk drives, Blu-ray disk drives,RAID systems, and digital versatile disk (DVD) drives.

The coded instructions 832 of FIGS. 3-7 may be stored in the massstorage device 828, in the volatile memory 814, in the non-volatilememory 816, and/or on a removable tangible computer readable storagemedium such as a CD or DVD.

While the examples disclosed herein are described as being implementedon server hardware, any other type of hardware resources may beutilized. For example, the example methods and apparatus disclosedherein may be implemented on any combination of servers, desktopcomputing devices, laptop computing devices, mobile computing devices,etc.

From the foregoing, it will be appreciated that some of the examplemethods and apparatus disclosed herein facilitate selection of avirtualization environment for a virtualized application (e.g., aworkload). In some example methods and apparatus, a virtualizationenvironment is selected and a workload is deployed in the selectedvirtualization environment to reduce the amount of computing resourcesthat would be utilized by executing the workload in a less-optimalvirtualization environment. For example, example methods and apparatusanalyze characteristics of the workload and characteristics of thevirtualization environments to select among full virtualizationenvironments, paravirtualized environments, and operation systemvirtualization environments. In some such examples, the characteristicsinclude determining an amount of computing resources needed forexecuting the workload and comparing the amount of computing resourcesto the amount of computing resources available in a data center. Whenthe data center includes sufficient computing resources, all threevirtualization environment types are scored equally. However, when thedata center does not include sufficient computing resources to meet thedemands of the workload, the operating system virtualization environmentis selected because it can more efficiently allocate the sharedresources of the data center for use in executing the workload. Thus,applying example methods and apparatus disclosed herein duringdeployment of new workloads or transition of already deployed workloadsresults in more efficient utilization of computing resources of a datacenter by selecting a virtualization environment that is determined tobe optimal. Furthermore, a platform management solution implementedaccording to the methods and apparatus disclosed herein canautomatically (e.g., upon deployment, periodically, aperiodically, etc.)migrate a workload from one platform to another to optimally utilize theresources of a datacenter.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

What is claimed is:
 1. A method comprising: determining, via aprocessor, characteristics of a virtualized application that is deployedin an existing virtualization environment; analyzing, via the processor,the characteristics of the virtualized application to select a subset ofvirtualization environments that are capable of executing thevirtualized application, the subset of virtualization environmentsselected from a set of virtualization environments of differentvirtualization environment types used in the datacenter; comparing, viathe processor, the characteristics of the virtualized application to thevirtualization environments of the subset of virtualization environmentsto determine scores for the virtualization environments; and migrate thevirtualized application from the existing virtualization environment toa new virtualization environment based on the scores.
 2. A method asdefined in claim 1, wherein determining the characteristics comprisesdetermining an amount of computing resources for the virtualizedapplication.
 3. A method as defined in claim 2, wherein comparing thecharacteristics of the virtualization environments comprises comparingan amount of computing resources for the virtualized application to anamount of computing resources available in the virtualizationenvironments.
 4. A method as defined in claim 1, further comprisingaccessing stored assessment configuration data to determine a set ofassessment criteria to be used in determining the scores.
 5. A method asdefined in claim 1, further comprising determining if the virtualizedapplication includes a plurality of virtualized applications to bedeployed using the same operating system.
 6. A method as defined inclaim 5, further comprising, when the virtualized application includesthe plurality of virtualized applications to be deployed, increasing, bya first amount, a first score for a first virtualization environmentthat utilizes operating system virtualization, the first amount beinggreater than a second amount by which a second score is increased for asecond virtualization environment that utilizes full virtualization. 7.A method as defined in claim 1, wherein determining the characteristicsfor the virtualized application includes obtaining user input regardingthe execution of the virtualized application.
 8. A method as defined inclaim 1, wherein the virtualization environment types include fullvirtualization, paravirtualization, and operation system virtualization.9. An apparatus comprising: a workload analyzer to determinecharacteristics of a virtualized application that is deployed in anexisting virtualization environment; a feasibility analyzer to analyzethe characteristics of the virtualized application to select a subset ofvirtualization environments that are capable of executing thevirtualized application, the subset of virtualization environmentsselected from a set of virtualization environments of differentvirtualization environment types used in the datacenter; a scoregenerator to compare the characteristics of the virtualized applicationto the virtualization environments of the subset of virtualizationenvironments to determine scores for the virtualization environments;and a workload migrator to migrate the virtualized application from theexisting virtualization environment to a new virtualization environmentbased on the scores.
 10. An apparatus as defined in claim 9, wherein theworkload analyzer is to determine the characteristics by determining anamount of computing resources available in the virtualized application.11. An apparatus as defined in claim 10, wherein the score generator isto compare the characteristics of the virtualization environmentscomprises comparing an amount of computing resources for the virtualizedapplication to an amount of computing resources for the virtualizationenvironments.
 12. An apparatus as defined in claim 9, wherein the scoregenerator is to access stored assessment configuration data to determinea set of assessment criteria to be used in determining the scores. 13.An apparatus as defined in claim 9, wherein the workload analyzer is todetermine if the virtualized application includes a plurality ofvirtualized applications to be deployed using the same operating system.14. An apparatus as defined in claim 13, wherein the score generator isto, when the virtualized application includes the plurality ofvirtualized applications to be deployed, increase, by a first amount, afirst score for a first virtualization environment that utilizesoperating system virtualization, the first amount being greater than asecond amount by which a second score is increased for a secondvirtualization environment that utilizes full virtualization.
 15. Anapparatus as defined in claim 9, wherein the workload analyzer is todetermine the characteristics for the virtualized application byobtaining user input regarding the execution of the virtualizedapplication.
 16. An apparatus as defined in claim 9, wherein thevirtualization environment types include full virtualization,paravirtualization, and operation system virtualization.
 17. A tangiblecomputer readable storage medium comprising instructions that, whenexecuted, cause a machine to at least: determine, via a processor,characteristics of a virtualized application that is deployed in anexisting virtualization environment; analyze, via the processor, thecharacteristics of the virtualized application to select a subset ofvirtualization environments that are capable of executing thevirtualized application, the subset of virtualization environmentsselected from a set of virtualization environments of differentvirtualization environment types used in the datacenter; compare, viathe processor, the characteristics of the virtualized application to thevirtualization environments of the subset of virtualization environmentsto determine scores for the virtualization environments; and migrate thevirtualized application from the existing virtualization environment toa new virtualization environment based on the scores.
 18. A tangiblecomputer readable storage medium as defined in claim 17, wherein theinstructions, when executed, cause the machine to determine thecharacteristics by determining an amount of computing resourcesavailable in the virtualized application.
 19. A tangible computerreadable storage medium as defined in claim 18, wherein theinstructions, when executed, cause the machine to compare thecharacteristics of the virtualization environments by comparing anamount of computing resources for the virtualized application to anamount of computing resources for the virtualization environments.
 20. Atangible computer readable storage medium as defined in claim 17,wherein the instructions, when executed, cause the machine to accessstored assessment configuration data to determine a set of assessmentcriteria to be used in determining the scores.
 21. A tangible computerreadable storage medium as defined in claim 17, wherein theinstructions, when executed, cause the machine to determine if thevirtualized application includes a plurality of virtualized applicationsto be deployed using the same operating system.
 22. A tangible computerreadable storage medium as defined in claim 21, wherein theinstructions, when executed, cause the machine to, when the virtualizedapplication includes the plurality of virtualized applications to bedeployed, increase, by a first amount, a first score for a firstvirtualization environment that utilizes operating systemvirtualization, the first amount being greater than a second amount bywhich a second score is increased for a second virtualizationenvironment that utilizes full virtualization.
 23. A tangible computerreadable storage medium as defined in claim 17, wherein theinstructions, when executed, cause the machine to determine thecharacteristics for the virtualized application by obtaining user inputregarding the execution of the virtualized application.
 24. A tangiblecomputer readable storage medium as defined in claim 17, wherein thevirtualization environment types include full virtualization,paravirtualization, and operation system virtualization.